Radiometric consistency assessment of hyperspectral infrared sounders

Abstract. The radiometric and spectral consistency among the Atmospheric Infrared Sounder (AIRS), the Infrared Atmospheric Sounding Interferometer (IASI), and the Cross-track Infrared Sounder (CrIS) is fundamental for the creation of long-term infrared (IR) hyperspectral radiance benchmark datasets for both inter-calibration and climate-related studies. In this study, the CrIS radiance measurements on Suomi National Polar-orbiting Partnership (SNPP) satellite are directly compared with IASI on MetOp-A and -B at the finest spectral scale and with AIRS on Aqua in 25 selected spectral regions through one year of simultaneous nadir overpass (SNO) observations to evaluate radiometric consistency of these four hyperspectral IR sounders. The spectra from different sounders are paired together through strict spatial and temporal collocation. The uniform scenes are selected by examining the collocated Visible Infrared Imaging Radiometer Suite (VIIRS) pixels. Their brightness temperature (BT) differences are then calculated by converting the spectra onto common spectral grids. The results indicate that CrIS agrees well with IASI on MetOp-A and IASI on MetOp-B at the longwave IR (LWIR) and middle-wave IR (MWIR) bands with 0.1–0.2 K differences. There are no apparent scene-dependent patterns for BT differences between CrIS and IASI for individual spectral channels. CrIS and AIRS are compared at the 25 spectral regions for both Polar and Tropical SNOs. The combined global SNO datasets indicate that, the CrIS-AIRS BT differences are less than or around 0.1 K among 21 of 25 comparison spectral regions and they range from 0.15 to 0.21 K in the remaining 4 spectral regions. CrIS-AIRS BT differences in some comparison spectral regions show weak scene-dependent features.

Download Full-text

Radiometric consistency assessment of hyperspectral infrared sounders

Atmospheric Measurement Techniques ◽

10.5194/amt-8-4831-2015 ◽

2015 ◽

Vol 8 (11) ◽

pp. 4831-4844 ◽

Cited By ~ 19

Author(s):

L. Wang ◽

Y. Han ◽

X. Jin ◽

Y. Chen ◽

D. A. Tremblay

Keyword(s):

Infrared Imaging ◽

Data Sets ◽

Atmospheric Infrared Sounder ◽

Benchmark Data ◽

Long Wave ◽

Atmospheric Sounding ◽

Spectral Scale ◽

Cross Track ◽

Spectral Channels

Abstract. The radiometric and spectral consistency among the Atmospheric Infrared Sounder (AIRS), the Infrared Atmospheric Sounding Interferometer (IASI), and the Cross-track Infrared Sounder (CrIS) is fundamental for the creation of long-term infrared (IR) hyperspectral radiance benchmark data sets for both intercalibration and climate-related studies. In this study, the CrIS radiance measurements on Suomi National Polar-orbiting Partnership (SNPP) satellite are directly compared with IASI on MetOp-A and MetOp-B at the finest spectral scale and with AIRS on Aqua in 25 selected spectral regions through simultaneous nadir overpass (SNO) observations in 2013, to evaluate radiometric consistency of these four hyperspectral IR sounders. The spectra from different sounders are paired together through strict spatial and temporal collocation. The uniform scenes are selected by examining the collocated Visible Infrared Imaging Radiometer Suite (VIIRS) pixels. Their brightness temperature (BT) differences are then calculated by converting the spectra onto common spectral grids. The results indicate that CrIS agrees well with IASI on MetOp-A and IASI on MetOp-B at the long-wave IR (LWIR) and middle-wave IR (MWIR) bands with 0.1–0.2 K differences. There are no apparent scene-dependent patterns for BT differences between CrIS and IASI for individual spectral channels. CrIS and AIRS are compared at the 25 spectral regions for both polar and tropical SNOs. The combined global SNO data sets indicate that the CrIS–AIRS BT differences are less than or around 0.1 K among 21 of 25 spectral regions and they range from 0.15 to 0.21 K in the remaining four spectral regions. CrIS–AIRS BT differences in some comparison spectral regions show weak scene-dependent features.

Download Full-text

Comparison of AIRS and IASI Radiances Using GOES Imagers as Transfer Radiometers toward Climate Data Records

Journal of Applied Meteorology and Climatology ◽

10.1175/2009jamc2218.1 ◽

2010 ◽

Vol 49 (3) ◽

pp. 478-492 ◽

Cited By ~ 40

Author(s):

Likun Wang ◽

Xiangqian Wu ◽

Mitch Goldberg ◽

Changyong Cao ◽

Yaping Li ◽

...

Keyword(s):

Brightness Temperature ◽

Climate Data ◽

Atmospheric Infrared Sounder ◽

Mean Values ◽

Tropical Regions ◽

Time Period ◽

Double Differences ◽

Cross Track ◽

Spectral Channels

Abstract The Atmospheric Infrared Sounder (AIRS) and the Infrared Atmospheric Sounding Interferometer (IASI), together with the future Cross-track Infrared Sounder, will provide long-term hyperspectral measurements of the earth and its atmosphere at ∼10 km spatial resolution. Quantifying the radiometric difference between AIRS and IASI is crucial for creating fundamental climate data records and establishing the space-based infrared calibration standard. Since AIRS and IASI have different local equator crossing times, a direct comparison of these two instruments over the tropical regions is not feasible. Using the Geostationary Operational Environmental Satellite (GOES) imagers as transfer radiometers, this study compares AIRS and IASI over warm scenes in the tropical regions for a time period of 16 months. The double differences between AIRS and IASI radiance biases relative to the GOES-11 and -12 imagers are used to quantify the radiance differences between AIRS and IASI within the GOES imager spectral channels. The results indicate that, at the 95% confidence level, the mean values of the IASI − AIRS brightness temperature differences for warm scenes are very small, that is, −0.0641 ± 0.0074 K, −0.0432 ± 0.0114 K, and −0.0095 ± 0.0151 K for the GOES-11 6.7-, 10.7-, and 12.0-μm channels, respectively, and −0.0490 ± 0.0100 K, −0.0419 ± 0.0224 K, and −0.0884 ± 0.0160 K for the GOES-12 6.5-, 10.7-, and 13.3-μm channels, respectively. The brightness temperature biases between AIRS and IASI within the GOES imager spectral range are less than 0.1 K although the AIRS measurements are slightly warmer than those of IASI.

Download Full-text

Uncertainty Characterization and Propagation in the Community Long-Term Infrared Microwave Combined Atmospheric Product System (CLIMCAPS)

Remote Sensing ◽

10.3390/rs11101227 ◽

2019 ◽

Vol 11 (10) ◽

pp. 1227 ◽

Cited By ~ 8

Author(s):

Nadia Smith ◽

Christopher D. Barnet

Keyword(s):

Uncertainty Propagation ◽

State Variables ◽

Product System ◽

Atmospheric Infrared Sounder ◽

Cloud Properties ◽

Infrared Measurements ◽

Highly Correlated ◽

Cross Track ◽

Correlated Signals

The Community Long-term Infrared Microwave Combined Atmospheric Product System (CLIMCAPS) retrieves multiple Essential Climate Variables (ECV) about the vertical atmosphere from hyperspectral infrared measurements made by the Atmospheric InfraRed Sounder (AIRS, 2002–present) and its successor, the Cross-track Infrared Sounder (CrIS, 2011–present). CLIMCAPS ECVs are profiles of temperature and water vapor, column amounts of greenhouse gases (CO2, CH4), ozone (O3) and precursor gases (CO, SO2) as well as cloud properties. AIRS (and CrIS) spectral measurements are highly correlated signals of many atmospheric state variables. CLIMCAPS inverts an AIRS (and CrIS) measurement into a set of discrete ECVs by employing a sequential Bayesian approach in which scene-dependent uncertainty is rigorously propagated. This not only linearizes the inversion problem but explicitly accounts for spectral interference from other state variables so that the correlation among ECVs (and their uncertainty) may be minimized. Here, we outline the CLIMCAPS retrieval methodology with specific focus given to its sequential scene-dependent uncertainty propagation system. We conclude by demonstrating continuity in two CLIMCAPS ECVs across AIRS and CrIS so that a long-term data record may be generated to study the feedback cycles characterizing our climate system.

Download Full-text

NH3 emissions from large point sources derived from CrIS and IASI satellite observations

Atmospheric Chemistry and Physics ◽

10.5194/acp-19-12261-2019 ◽

2019 ◽

Vol 19 (19) ◽

pp. 12261-12293 ◽

Cited By ~ 9

Author(s):

Enrico Dammers ◽

Chris A. McLinden ◽

Debora Griffin ◽

Mark W. Shephard ◽

Shelley Van Der Graaf ◽

...

Keyword(s):

Human Health ◽

Reactive Nitrogen Species ◽

Point Sources ◽

Satellite Observations ◽

Atmospheric Sounding ◽

Order Of Magnitude ◽

Short And Long Term ◽

Current Emission ◽

Cross Track

Abstract. Ammonia (NH3) is an essential reactive nitrogen species in the biosphere and through its use in agriculture in the form of fertilizer (important for sustaining humankind). The current emission levels, however, are up to 4 times higher than in the previous century and continue to grow with uncertain consequences to human health and the environment. While NH3 at its current levels is a hazard to environmental and human health, the atmospheric budget is still highly uncertain, which is a product of an overall lack of measurements. The capability to measure NH3 with satellites has opened up new ways to study the atmospheric NH3 budget. In this study, we present the first estimates of NH3 emissions, lifetimes and plume widths from large (>∼5 kt yr−1) agricultural and industrial point sources from Cross-track Infrared Sounder (CrIS) satellite observations across the globe with a consistent methodology. The same methodology is also applied to the Infrared Atmospheric Sounding Interferometer (IASI) (A and B) satellite observations, and we show that the satellites typically provide comparable results that are within the uncertainty of the estimates. The computed NH3 lifetime for large point sources is on average 2.35±1.16 h. For the 249 sources with emission levels detectable by the CrIS satellite, there are currently 55 locations missing (or underestimated by more than an order of magnitude) from the current Hemispheric Transport Atmospheric Pollution version 2 (HTAPv2) emission inventory and only 72 locations with emissions within a factor of 2 compared to the inventories. The CrIS emission estimates give a total of 5622 kt yr−1, for the sources analyzed in this study, which is around a factor of ∼2.5 higher than the emissions reported in HTAPv2. Furthermore, the study shows that it is possible to accurately detect short- and long-term changes in emissions, demonstrating the possibility of using satellite-observed NH3 to constrain emission inventories.

Download Full-text

NOAA-20 and S-NPP VIIRS Thermal Emissive Bands On-Orbit Calibration Algorithm Update and Long-Term Performance Inter-Comparison

Remote Sensing ◽

10.3390/rs13030448 ◽

2021 ◽

Vol 13 (3) ◽

pp. 448

Author(s):

Wenhui Wang ◽

Changyong Cao

Keyword(s):

Bias Correction ◽

Infrared Imaging ◽

Sensor Data ◽

Warm Up ◽

User Communities ◽

Calibration Algorithm ◽

Long Term Performance ◽

Cross Track ◽

Term Performance

The Visible Infrared Imaging Radiometer Suite (VIIRS) on board the National Oceanic and Atmospheric Administration-20 (NOAA-20) and the Suomi National Polar-orbiting Partnership Program (S-NPP) satellites were launched in late 2017 and 2011, respectively. This paper presents a recent update in the VIIRS thermal emissive bands (TEB) on-orbit calibration algorithm and inter-compares long-term instrument and TEB sensor data records (SDR) performances of the two VIIRS, to support user communities. The VIIRS TEB calibration algorithm was improved to mitigate calibration biases during the blackbody warm-up/cool-down (WUCD) events. Four WUCD bias correction methods were implemented in the NOAA operational processing in 2019: (1) the Nominal-F method, (2) the WUCD-C method, (3) the Ltrace method, and (4) the Ltrace-2 method. Our evaluation results indicate that the on-orbit performances of the two VIIRS instruments have been generally stable and comparable with each other, except that NOAA-20 VIIRS blackbody and instrument temperatures are lower than those of the S-NPP VIIRS. The degradations in the S-NPP TEB detector responsivities remain small after 9 years on-orbit. NOAA-20 detector responsivities have been generally stable after the longwave infrared degradation during its early mission was resolved by the mid-mission outgassing. NOAA-20 and S-NPP VIIRS TEB SDRs agree with co-located Cross-track Infrared Sounder observations, with daily averaged biases within 0.1 K at nadir. After the implementation of operational WUCD bias correction, residual TEB WUCD biases are similar for NOAA-20 and S-NPP, with daily averaged biases ~0.01 K in all bands.

Download Full-text

Monitoring precipitation convective clouds with collocated hyperspectral infrared sounder and imager measurements

10.5194/egusphere-egu2020-10381 ◽

2020 ◽

Author(s):

Xinya Gong ◽

Jun Li ◽

Zhenglong Li ◽

Christopher C. Moeller

Keyword(s):

Brightness Temperature ◽

Infrared Imaging ◽

Water Vapor Absorption ◽

Mean Values ◽

Convective Clouds ◽

Vapor Absorption ◽

Absorption Channel ◽

Cross Track ◽

High Clouds ◽

Meteorological Satellite

Typically, DCCs are identified by 11 &#181;m band brightness temperature (BT11) lower than a fixed BT threshold. Another method of combining the brightness temperature difference (BTD) between a water vapor absorption channel and a window channel to its measurement noise ratio (BNR) is adopted and applied to DCC identification. This BNR method improves the DCC detections over the legacy method because it is less contaminated with high clouds not thick and bright enough. BNR detects fewer DCCs than BT11, but with more confidence.&#160;Using observations of the collocated Cross-track Infrared Sounder (CrIS) and the Visible Infrared Imaging Radiometer Suite (VIIRS) onboard the Suomi National Polar-orbiting Partnership (SNPP) from 2017 to 2018, the results show BNR has better performances than BT11 for identifying the DCC and monitoring reflective solar bands. When comparing to BT11, BNR has more robust and invariant time series of monthly reflectance for all RSBs. Because BNR affects more on the left tails (less reflective) of the histograms than the mode reflectance, the improvement is more significant on the mean values than the modes. This method can be applied to other imagers with collocated advanced infrared sounders for detecting DCCs and monitoring the calibration stabilities of RSBs.&#160;Recently, the hyperspectral infrared atmospheric sounders onboard China&#8217;s next-generation FengYun satellites, i.e. the Geosynchronous Interferometric InfraRed Sounder (GIIRS) on the FengYun-4 geostationary satellite series and the Hyperspectral Infrared Atmospheric Sounder (HIRAS) on the FengYun-3 polar orbiting meteorological satellite series, are in operation. Flown onboard the same platforms, the collocated (consistent in time and space) infrared sounders and imagers, provide mount of match-up measurements for the study of methodology and process for synergistic use of both infrared sounder and imager for multiple applications. The findings will provide scientific evidences for further enhancements and applications of future FengYun satellites and its observing system.

Download Full-text

A New 32-Day Average-Difference Method for Calculating Inter-Sensor Calibration Radiometric Biases between SNPP and NOAA-20 Instruments within ICVS Framework

Remote Sensing ◽

10.3390/rs13163079 ◽

2021 ◽

Vol 13 (16) ◽

pp. 3079

Author(s):

Banghua Yan ◽

Mitch Goldberg ◽

Xin Jin ◽

Ding Liang ◽

Jingfeng Huang ◽

...

Keyword(s):

Infrared Imaging ◽

Satellite System ◽

Advanced Technology ◽

New Method ◽

Double Difference ◽

Sensor Calibration ◽

Long Term Trends ◽

Cross Track ◽

Radiative Transfer Modeling

Two existing double-difference (DD) methods, using either a 3rdSensor or Radiative Transfer Modeling (RTM) as a transfer, are applicable primarily for limited regions and channels, and, thus critical in capturing inter-sensor calibration radiometric bias features. A supplementary method is also desirable for estimating inter-sensor calibration biases at the window and lower sounding channels where the DD methods have non-negligible errors. In this study, using the Suomi National Polar-orbiting Partnership (SNPP) and Joint Polar Satellite System (JPSS)-1 (alias NOAA-20) as an example, we present a new inter-sensor bias statistical method by calculating 32-day averaged differences (32D-AD) of radiometric measurements between the same instrument onboard two satellites. In the new method, a quality control (QC) scheme using one-sigma (for radiance difference), or two-sigma (for radiance) thresholds are established to remove outliers that are significantly affected by diurnal biases within the 32-day temporal coverage. The performance of the method is assessed by applying it to estimate inter-sensor calibration radiometric biases for four instruments onboard SNPP and NOAA-20, i.e., Advanced Technology Microwave Sounder (ATMS), Cross-track Infrared Sounder (CrIS), Nadir Profiler (NP) within the Ozone Mapping and Profiler Suite (OMPS), and Visible Infrared Imaging Radiometer Suite (VIIRS). Our analyses indicate that the globally-averaged inter-sensor differences using the 32D-AD method agree with those using the existing DD methods for available channels, with margins partially due to remaining diurnal errors. In addition, the new method shows its capability in assessing zonal mean features of inter-sensor calibration biases at upper sounding channels. It also detects the solar intrusion anomaly occurring on NOAA-20 OMPS NP at wavelengths below 300 nm over the Northern Hemisphere. Currently, the new method is being operationally adopted to monitor the long-term trends of (globally-averaged) inter-sensor calibration radiometric biases at all channels for the above sensors in the Integrated Calibration/Validation System (ICVS). It is valuable in demonstrating the quality consistencies of the SDR data at the four instruments between SNPP and NOAA-20 in long-term statistics. The methodology is also applicable for other POES cross-sensor calibration bias assessments with minor changes.

Download Full-text